Paper Info
Title
Eco-driving of electric vehicles with integrated motion and battery dynamics
Abstract
Considering the great potential of electric vehicles (EVs) in relieving energy and environmental crisis, this paper proposes an integrated motion and battery control method for the eco-driving of EVs. The goals are to satisfy the power demand of certain driving cycles with minimal energy consumption and to guarantee safe operations of the battery at the same time. Specifically, we consider both the vehicle level motion dynamics and the battery dynamics for an integrated EV eco-driving model. Model predictive control (MPC) is utilized to handle the multiple conflicting objectives and system constraints. To reduce the possible heavy computational burden of the online optimization problems, a successive linearization approach in the framework of MPC is applied to the prediction model to achieve a trade-off between control performance and computational complexity. Standard driving cycles are employed to test the effectiveness of the proposed algorithms. Simulation results show that the integrated motion and battery control can achieve the eco-driving goals in various test scenarios.
Year
DOI
Venue
2019
10.1109/ICNSC.2019.8743183
2019 IEEE 16th International Conference on Networking, Sensing and Control (ICNSC)
Keywords
Field
DocType
Eco-driving,electric vehicles,integrated dynamics,model predictive control
Control theory,Computer science,Model predictive control,Control engineering,Online optimization,Scenario testing,Battery (electricity),Motion dynamics,Energy consumption,Linearization,Computational complexity theory
Conference
ISSN
ISBN
Citations 
1810-7869
978-1-7281-0085-2
0
PageRank 
References 
Authors
0.34
7
5
Name
Order
Citations
PageRank
Huarong Zheng131.39
Jun Wu245675.01
Weimin Wu323643.97
Yifeng Zhang4183.85
Yi-Sheng Huang530926.16